We have focussed on developing datasets for gene expression using RNA-Seq, which allows us to apply a standard set of methods to a variety of model systems. Using this approach we have contributed to a number of different studies, including examination of mouse brain development or aging in non-human primates. One of the most interesting areas is in the application to the human brain, where we have a large series of brains with information on both genetic variability and gene expression. Our data has been used in many studies to determine whether a nominated genetic variant associated with a given disease or other phenotype, has a proximal biological effect on gene expression. We are currently extending this work to provide more samples and a deeper view of gene expression.